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Count-Based Exploration with Neural Density Models

Count-Based Exploration with Neural Density Models

3 March 2017
Georg Ostrovski
Marc G. Bellemare
Aaron van den Oord
Rémi Munos
ArXivPDFHTML

Papers citing "Count-Based Exploration with Neural Density Models"

50 / 117 papers shown
Title
Reinforcement Learning with Action-Free Pre-Training from Videos
Reinforcement Learning with Action-Free Pre-Training from Videos
Younggyo Seo
Kimin Lee
Stephen James
Pieter Abbeel
SSL
OnRL
18
117
0
25 Mar 2022
Rényi State Entropy for Exploration Acceleration in Reinforcement
  Learning
Rényi State Entropy for Exploration Acceleration in Reinforcement Learning
Mingqi Yuan
Man-On Pun
Dong Wang
19
23
0
08 Mar 2022
Collaborative Training of Heterogeneous Reinforcement Learning Agents in
  Environments with Sparse Rewards: What and When to Share?
Collaborative Training of Heterogeneous Reinforcement Learning Agents in Environments with Sparse Rewards: What and When to Share?
Alain Andres
Esther Villar-Rodriguez
Javier Del Ser
22
9
0
24 Feb 2022
Learning Causal Overhypotheses through Exploration in Children and
  Computational Models
Learning Causal Overhypotheses through Exploration in Children and Computational Models
Eliza Kosoy
Adrian Liu
Jasmine Collins
David M. Chan
Jessica B. Hamrick
Nan Rosemary Ke
Sandy H Huang
Bryanna Kaufmann
John F. Canny
Alison Gopnik
CML
22
9
0
21 Feb 2022
Generative Adversarial Exploration for Reinforcement Learning
Generative Adversarial Exploration for Reinforcement Learning
Weijun Hong
Menghui Zhu
Minghuan Liu
Weinan Zhang
Ming Zhou
Yong Yu
Peng Sun
OnRL
39
7
0
27 Jan 2022
Learning to Act with Affordance-Aware Multimodal Neural SLAM
Learning to Act with Affordance-Aware Multimodal Neural SLAM
Zhiwei Jia
Kaixiang Lin
Yizhou Zhao
Qiaozi Gao
Govind Thattai
Gaurav Sukhatme
LM&Ro
31
15
0
24 Jan 2022
Interesting Object, Curious Agent: Learning Task-Agnostic Exploration
Interesting Object, Curious Agent: Learning Task-Agnostic Exploration
Simone Parisi
Victoria Dean
Deepak Pathak
Abhinav Gupta
LM&Ro
38
50
0
25 Nov 2021
Episodic Multi-agent Reinforcement Learning with Curiosity-Driven
  Exploration
Episodic Multi-agent Reinforcement Learning with Curiosity-Driven Exploration
Lu Zheng
Jiarui Chen
Jianhao Wang
Jiamin He
Yujing Hu
Yingfeng Chen
Changjie Fan
Yang Gao
Chongjie Zhang
16
82
0
22 Nov 2021
Anti-Concentrated Confidence Bonuses for Scalable Exploration
Anti-Concentrated Confidence Bonuses for Scalable Exploration
Jordan T. Ash
Cyril Zhang
Surbhi Goel
A. Krishnamurthy
Sham Kakade
43
6
0
21 Oct 2021
Seeking Visual Discomfort: Curiosity-driven Representations for
  Reinforcement Learning
Seeking Visual Discomfort: Curiosity-driven Representations for Reinforcement Learning
Elie Aljalbout
Maximilian Ulmer
Rudolph Triebel
16
2
0
02 Oct 2021
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative
  Survey
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey
Amjad Yousef Majid
Serge Saaybi
Tomas van Rietbergen
Vincent François-Lavet
R. V. Prasad
Chris Verhoeven
OffRL
60
54
0
28 Sep 2021
Making Curiosity Explicit in Vision-based RL
Making Curiosity Explicit in Vision-based RL
Elie Aljalbout
Maximilian Ulmer
Rudolph Triebel
OffRL
26
2
0
28 Sep 2021
On Bonus-Based Exploration Methods in the Arcade Learning Environment
On Bonus-Based Exploration Methods in the Arcade Learning Environment
Adrien Ali Taïga
W. Fedus
Marlos C. Machado
Aaron Courville
Marc G. Bellemare
16
58
0
22 Sep 2021
Focus on Impact: Indoor Exploration with Intrinsic Motivation
Focus on Impact: Indoor Exploration with Intrinsic Motivation
Roberto Bigazzi
Federico Landi
S. Cascianelli
Lorenzo Baraldi
Marcella Cornia
Rita Cucchiara
OffRL
29
13
0
14 Sep 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to
  Multiagent Domain
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain
Jianye Hao
Tianpei Yang
Hongyao Tang
Chenjia Bai
Jinyi Liu
Zhaopeng Meng
Peng Liu
Zhen Wang
OffRL
36
92
0
14 Sep 2021
A Survey of Exploration Methods in Reinforcement Learning
A Survey of Exploration Methods in Reinforcement Learning
Susan Amin
Maziar Gomrokchi
Harsh Satija
H. V. Hoof
Doina Precup
OffRL
21
80
0
01 Sep 2021
When should agents explore?
When should agents explore?
Miruna Pislar
David Szepesvari
Georg Ostrovski
Diana Borsa
Tom Schaul
40
22
0
26 Aug 2021
Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
Cooperative Exploration for Multi-Agent Deep Reinforcement Learning
Iou-Jen Liu
Unnat Jain
Raymond A. Yeh
A. Schwing
39
104
0
23 Jul 2021
Offline Reinforcement Learning as Anti-Exploration
Offline Reinforcement Learning as Anti-Exploration
Shideh Rezaeifar
Robert Dadashi
Nino Vieillard
Léonard Hussenot
Olivier Bachem
Olivier Pietquin
M. Geist
OffRL
34
51
0
11 Jun 2021
Sample-efficient Reinforcement Learning Representation Learning with
  Curiosity Contrastive Forward Dynamics Model
Sample-efficient Reinforcement Learning Representation Learning with Curiosity Contrastive Forward Dynamics Model
Thanh Nguyen
Tung M. Luu
Thang Vu
Chang D. Yoo
15
17
0
15 Mar 2021
Behavior From the Void: Unsupervised Active Pre-Training
Behavior From the Void: Unsupervised Active Pre-Training
Hao Liu
Pieter Abbeel
VLM
SSL
41
195
0
08 Mar 2021
Decoupled Exploration and Exploitation Policies for Sample-Efficient
  Reinforcement Learning
Decoupled Exploration and Exploitation Policies for Sample-Efficient Reinforcement Learning
William F. Whitney
Michael Bloesch
Jost Tobias Springenberg
A. Abdolmaleki
Kyunghyun Cho
Martin Riedmiller
OffRL
29
13
0
23 Jan 2021
Geometric Entropic Exploration
Geometric Entropic Exploration
Z. Guo
M. G. Azar
Alaa Saade
S. Thakoor
Bilal Piot
Bernardo Avila-Pires
Michal Valko
Thomas Mesnard
Tor Lattimore
Rémi Munos
35
30
0
06 Jan 2021
BeBold: Exploration Beyond the Boundary of Explored Regions
BeBold: Exploration Beyond the Boundary of Explored Regions
Tianjun Zhang
Huazhe Xu
Xiaolong Wang
Yi Wu
Kurt Keutzer
Joseph E. Gonzalez
Yuandong Tian
36
40
0
15 Dec 2020
Latent World Models For Intrinsically Motivated Exploration
Latent World Models For Intrinsically Motivated Exploration
Aleksandr Ermolov
N. Sebe
25
25
0
05 Oct 2020
Novelty Search in Representational Space for Sample Efficient
  Exploration
Novelty Search in Representational Space for Sample Efficient Exploration
Ruo Yu Tao
Vincent François-Lavet
Joelle Pineau
30
43
0
28 Sep 2020
Learning Abstract Models for Strategic Exploration and Fast Reward
  Transfer
Learning Abstract Models for Strategic Exploration and Fast Reward Transfer
E. Liu
Ramtin Keramati
Sudarshan Seshadri
Kelvin Guu
Panupong Pasupat
Emma Brunskill
Percy Liang
OffRL
19
5
0
12 Jul 2020
Learning with AMIGo: Adversarially Motivated Intrinsic Goals
Learning with AMIGo: Adversarially Motivated Intrinsic Goals
Andres Campero
Roberta Raileanu
Heinrich Küttler
J. Tenenbaum
Tim Rocktaschel
Edward Grefenstette
38
125
0
22 Jun 2020
Non-local Policy Optimization via Diversity-regularized Collaborative
  Exploration
Non-local Policy Optimization via Diversity-regularized Collaborative Exploration
Zhenghao Peng
Hao Sun
Bolei Zhou
15
18
0
14 Jun 2020
Adaptive Reward-Free Exploration
Adaptive Reward-Free Exploration
E. Kaufmann
Pierre Ménard
O. D. Domingues
Anders Jonsson
Edouard Leurent
Michal Valko
30
79
0
11 Jun 2020
Novel Policy Seeking with Constrained Optimization
Novel Policy Seeking with Constrained Optimization
Hao Sun
Zhenghao Peng
Bo Dai
Jian Guo
Dahua Lin
Bolei Zhou
16
13
0
21 May 2020
Planning to Explore via Self-Supervised World Models
Planning to Explore via Self-Supervised World Models
Ramanan Sekar
Oleh Rybkin
Kostas Daniilidis
Pieter Abbeel
Danijar Hafner
Deepak Pathak
SSL
27
397
0
12 May 2020
First return, then explore
First return, then explore
Adrien Ecoffet
Joost Huizinga
Joel Lehman
Kenneth O. Stanley
Jeff Clune
47
349
0
27 Apr 2020
Agent57: Outperforming the Atari Human Benchmark
Agent57: Outperforming the Atari Human Benchmark
Adria Puigdomenech Badia
Bilal Piot
Steven Kapturowski
Pablo Sprechmann
Alex Vitvitskyi
Daniel Guo
Charles Blundell
OffRL
13
509
0
30 Mar 2020
Ready Policy One: World Building Through Active Learning
Ready Policy One: World Building Through Active Learning
Philip J. Ball
Jack Parker-Holder
Aldo Pacchiano
K. Choromanski
Stephen J. Roberts
OffRL
29
49
0
07 Feb 2020
Q-Learning in enormous action spaces via amortized approximate
  maximization
Q-Learning in enormous action spaces via amortized approximate maximization
T. Wiele
David Warde-Farley
A. Mnih
Volodymyr Mnih
23
59
0
22 Jan 2020
An Exploration of Embodied Visual Exploration
An Exploration of Embodied Visual Exploration
Santhosh Kumar Ramakrishnan
Dinesh Jayaraman
Kristen Grauman
LM&Ro
30
98
0
07 Jan 2020
A Survey of Deep Reinforcement Learning in Video Games
A Survey of Deep Reinforcement Learning in Video Games
Kun Shao
Zhentao Tang
Yuanheng Zhu
Nannan Li
Dongbin Zhao
OffRL
AI4TS
37
188
0
23 Dec 2019
Implicit Generative Modeling for Efficient Exploration
Implicit Generative Modeling for Efficient Exploration
Neale Ratzlaff
Qinxun Bai
Fuxin Li
Wenyuan Xu
22
12
0
19 Nov 2019
Multi-Path Policy Optimization
Multi-Path Policy Optimization
L. Pan
Qingpeng Cai
Longbo Huang
18
2
0
11 Nov 2019
Explicit Explore-Exploit Algorithms in Continuous State Spaces
Explicit Explore-Exploit Algorithms in Continuous State Spaces
Mikael Henaff
OffRL
14
31
0
01 Nov 2019
Influence-Based Multi-Agent Exploration
Influence-Based Multi-Agent Exploration
Tonghan Wang
Jianhao Wang
Yi Wu
Chongjie Zhang
16
137
0
12 Oct 2019
Receding Horizon Curiosity
Receding Horizon Curiosity
M. Schultheis
Boris Belousov
Hany Abdulsamad
Jan Peters
17
15
0
08 Oct 2019
Is Deep Reinforcement Learning Really Superhuman on Atari? Leveling the
  playing field
Is Deep Reinforcement Learning Really Superhuman on Atari? Leveling the playing field
Marin Toromanoff
É. Wirbel
Fabien Moutarde
OffRL
22
24
0
13 Aug 2019
Optimistic Proximal Policy Optimization
Optimistic Proximal Policy Optimization
Takahisa Imagawa
Takuya Hiraoka
Yoshimasa Tsuruoka
15
4
0
25 Jun 2019
Deep Policies for Width-Based Planning in Pixel Domains
Deep Policies for Width-Based Planning in Pixel Domains
Miquel Junyent
Anders Jonsson
Vicencc Gómez
36
10
0
12 Apr 2019
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
Vitchyr H. Pong
Murtaza Dalal
Steven Lin
Ashvin Nair
Shikhar Bahl
Sergey Levine
OffRL
SSL
28
269
0
08 Mar 2019
World Discovery Models
World Discovery Models
M. G. Azar
Bilal Piot
Bernardo Avila-Pires
Jean-Bastien Grill
Florent Altché
Rémi Munos
21
26
0
20 Feb 2019
Amplifying the Imitation Effect for Reinforcement Learning of UCAV's
  Mission Execution
Amplifying the Imitation Effect for Reinforcement Learning of UCAV's Mission Execution
G. Lee
Chang Ouk Kim
8
4
0
17 Jan 2019
Malthusian Reinforcement Learning
Malthusian Reinforcement Learning
Joel Z Leibo
Julien Perolat
Edward Hughes
S. Wheelwright
Adam H. Marblestone
Edgar A. Duénez-Guzmán
P. Sunehag
Iain Dunning
T. Graepel
AI4CE
25
37
0
17 Dec 2018
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